﻿*Recoding from raw data to make variables lie between 0 and 1.

COMPUTE ValuesImportantDiv100=q2/100.
VARIABLE LABELS  ValuesImportantDiv100 'Values Important Div100'.
EXECUTE.

COMPUTE PastContributionsDiv100=q3/100.
VARIABLE LABELS  PastContributionsDiv100 'Past Contributions Div100'.
EXECUTE.

COMPUTE ProjectContributionsDiv100=q4/100.
VARIABLE LABELS  ProjectContributionsDiv100 'Projected Contributions Div100'.
EXECUTE.

COMPUTE PersBenefitsDiv100=q5/100.
VARIABLE LABELS  PersBenefitsDiv100 'Personal Benefits Div100'.
EXECUTE.

COMPUTE NationBenefitsDiv100=q6/100.
VARIABLE LABELS  NationBenefitsDiv100 'National Benefits Div100'.
EXECUTE.

COMPUTE AngerIngroupFRDiv100=q7/100.
VARIABLE LABELS  AngerIngroupFRDiv100 'Anger Ingroup Free Rider Div100'.
EXECUTE.

COMPUTE GratIngroupConDiv100=q8/100.
VARIABLE LABELS  GratIngroupConDiv100 'Gratitude Ingroup Contributor Div100'.
EXECUTE.

COMPUTE AngerOutgroupFRDiv100=q9/100.
VARIABLE LABELS  AngerOutgroupFRDiv100 'Anger Outgroup Free Rider Div100'.
EXECUTE.

COMPUTE GratOutgroupConDiv100=q10/100.
VARIABLE LABELS  GratOutgroupConDiv100 'Gratitude Outgroup Contributor Div100'.
EXECUTE.

COMPUTE AngerExiterDiv100=q11/100.
VARIABLE LABELS  AngerExiterDiv100 'Anger Exiter Div100'.
EXECUTE.

COMPUTE PosEncExiterDiv100=q12/100.
VARIABLE LABELS  PosEncExiterDiv100 'Positive Encouragement Exiter Div100'.
EXECUTE.

COMPUTE GratNewcomerDiv100=q13/100.
VARIABLE LABELS  GratNewcomerDiv100 'Grateful Newcomer Div100'.
EXECUTE.

COMPUTE AgeDiv100=ppage/100.
EXECUTE.

COMPUTE IncomeRecoded=(ppincimp-1)/18.
EXECUTE.

COMPUTE RightToLeftPoliticsRecoded=(RightToLeftPolitics+1)/2.
EXECUTE.

COMPUTE Education0To1=(ppeduc-1)/8.
EXECUTE.

*Generating descriptive stats.
FREQUENCIES VARIABLES=PartyInd partSex raceBlack raceOther raceHispanic raceTwoPlus 
  /ORDER=ANALYSIS.
DESCRIPTIVES VARIABLES=AgeDiv100 IncomeRecoded Education0To1 
  /STATISTICS=MEAN STDDEV MIN MAX.
FREQUENCIES VARIABLES=q1 
  /ORDER=ANALYSIS.

*Ancillary data analysis for supplement about the correlation between gratitude and positive encouragement.
CORRELATIONS 
  /VARIABLES=GratIngroupConDiv100 PosEncExiterDiv100 
  /PRINT=TWOTAIL NOSIG 
  /MISSING=PAIRWISE.
PARTIAL CORR 
  /VARIABLES=GratIngroupConDiv100 PosEncExiterDiv100 BY GratOutgroupConDiv100 
  /SIGNIFICANCE=TWOTAIL 
  /MISSING=LISTWISE.

*Analysis of whether party members are angrier at ingroup non-contributors, compared to independents.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT AngerIngroupFRDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100.

*Analysis of whether party members are more grateful at ingroup contributors, compared to independents.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT GratIngroupConDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100.

*Analysis of whether party members are angrier at outgroup non-contributors, compared to independents.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT AngerOutgroupFRDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerIngroupFRDiv100.

*Analysis of whether party members are more grateful at outgroup contributors, compared to independents.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT GratOutgroupConDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratIngroupConDiv100.

*ANOVA on Party Member/Independent X Ingroup/outgroup non-contributor; anger DV.
GLM AngerIngroupFRDiv100 AngerOutgroupFRDiv100 BY PartyInd WITH partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 
  /WSFACTOR=target 2 Polynomial 
  /METHOD=SSTYPE(3) 
  /PLOT=PROFILE(PartyInd*target target*PartyInd) 
  /PRINT=DESCRIPTIVE ETASQ 
  /CRITERIA=ALPHA(.05) 
  /WSDESIGN=target 
  /DESIGN=partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 PartyInd.

*ANOVA on Party Member/Independent X Ingroup/outgroup contributor; gratitude DV.
GLM GratIngroupConDiv100 GratOutgroupConDiv100 BY PartyInd WITH partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 
  /WSFACTOR=target 2 Polynomial 
  /METHOD=SSTYPE(3) 
  /PLOT=PROFILE(PartyInd*target target*PartyInd) 
  /PRINT=DESCRIPTIVE ETASQ 
  /CRITERIA=ALPHA(.05) 
  /WSDESIGN=target 
  /DESIGN=partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 PartyInd.

*Within party members and, separately, independents, are emotions more expressed at ingroup members.
SORT CASES  BY PartyInd. 
SPLIT FILE LAYERED BY PartyInd. 
T-TEST PAIRS=AngerIngroupFRDiv100 GratIngroupConDiv100 WITH AngerOutgroupFRDiv100 GratOutgroupConDiv100 (PAIRED) 
  /CRITERIA=CI(.9500) 
  /MISSING=ANALYSIS.
SPLIT FILE OFF.

*Predicting public goods perceptions from party member versus independent, separately with anger and gratitude controls.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT NationBenefitsDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT NationBenefitsDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100.

*Predicting personal benefits perceptions from party member versus independent, separately with anger and gratitude controls.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT PersBenefitsDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 NationBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100.
 REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT  PersBenefitsDiv100 
  /METHOD=ENTER PartyInd ValuesImportantDiv100 PastContributionsDiv100 NationBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100.

*Predicting personal benefits perceptions from values separately for party members and independents, separately with anger and gratitude controls.
SORT CASES  BY PartyInd.
SPLIT FILE LAYERED BY PartyInd.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT NationBenefitsDiv100 
  /METHOD=ENTER ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT NationBenefitsDiv100 
  /METHOD=ENTER ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100.
SPLIT FILE OFF.

*Predicting anger and gratitude from public goods perceptions.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT AngerIngroupFRDiv100 
  /METHOD=ENTER NationBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT GratIngroupConDiv100 
  /METHOD=ENTER NationBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100.


*Predicting anger and gratitude from public goods perceptions separately for party members and independents.
SORT CASES  BY PartyInd.
SPLIT FILE LAYERED BY PartyInd.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT AngerIngroupFRDiv100 
  /METHOD=ENTER NationBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100.
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT GratIngroupConDiv100 
  /METHOD=ENTER NationBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100.
SPLIT FILE OFF.

*Mediation analyses. "INDIRECT" plug-in by Andrew Hayes, version 4.2 was used, www.afhayes.com. The following codes was automatically generated by the plugin.
*Because these are bootstrap analyses and involve random sampling, recomputing may lead to slightly different numbers than reported in the paper.

/* Written by Andrew F. Hayes */.
/* http://www.afhayes.com */.
/* Version 4.2 */.
DEFINE INDIRECT (y = !charend('/')/x = !charend('/')/m = !charend('/')/c=!charend('/') !default(xxxxx)/
  boot =!charend('/') !default(1000)/conf = !charend('/') !default(95)/percent = !charend('/') !default(0)/bc = !charend('/')
  !default(1)/bca = !charend('/') !default(0)/normal = !charend ('/') !default(0)/contrast = !charend ('/') !default(0)/iterate = !charend('/') !default(10000)/converge =
  !charend('/') !default(.0000001)).
PRESERVE.
SET LENGTH = NONE.
SET MXLOOPS = 10000001.
SET SEED = RANDOM.
SET PRINTBACK = OFF.
MATRIX.
get dd/variables = !y !x !m/names = nm/MISSING = OMIT.
compute temp = ncol(dd).
get dd2/variables = !y !x NationBenefitsDiv100/MISSING = OMIT.
compute nc = ncol(dd)-ncol(dd2).
compute ovals = ncol(design(dd(:,1))).
do if (ovals = 2).
   compute omx = cmax(dd(:,1)).
   compute omn = cmin(dd(:,1)).
   compute dd(:,1) = (dd(:,1) = omx).
   compute rcd = {omn, 0; omx, 1}.
end if.
compute nm = t(nm).
compute outv = t(nm(1,1)).
compute n = nrow(dd).
compute nv = ncol(dd).
compute con = make(n,1,1).
compute dat2 = dd.
compute dat = dd.
compute bzx = make(nv-2-nc,1,0).
compute bzxse = make(nv-2-nc,1,0).
compute b=make((nv-1-nc),(nv-1-nc),0).
compute resid = make(n,(nv-nc),0).
compute info = make((2*(nv-nc-2)+1),(2*(nv-nc-2)+1),0).
compute imat = make(ncol(info),4,1).
compute imat(1:(nv-nc-2),1)=t({2:(nv-nc-1):1}).
compute imat(1:(nv-nc-2),3)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),2)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),4)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),1)=make((nv-nc-2),1,(nv-nc)).
compute imat((nv-nc-1):(ncol(info)-1),3)=make((nv-nc-2),1,(nv-nc)).
compute imat(ncol(info),:)={(nv-nc),1,(nv-nc),1}.
compute cname={"C1";"C2";"C3";"C4";"C5";"C6";"C7";"C8";"C9";"C10";"C11";"C12";"C13";"C14";"C15";"C16";"C17"}.
compute cname={cname;"C18";"C19";"C20";"C21";"C22";"C23";"C24";"C25";"C26";"C27";"C28";"C29";"C30";"C31"}.
compute cname={cname;"C32";"C33";"C34";"C35";"C36";"C37";"C38";"C39";"C40";"C41";"C42";"C43";"C44";"C45"}.
compute p0=-.322232431088.
compute p1 = -1.
compute p2 = -.342242088547.
compute p3 = -.0204231210245.
compute p4 = -.0000453642210148.
compute q0 = .0993484626060.
compute q1 = .588581570495.
compute q2 = .531103462366.
compute q3 = .103537752850.
compute q4 = .0038560700634.
compute conf = rnd(!conf).
compute lowalp = 0.5*(1-(conf/100)).
compute upalp = 0.5*(1+(conf/100)).
compute zbca = {lowalp; upalp}.
do if (!boot > 999).
   compute btn = trunc(!boot/1000)*1000.
   compute lpmax = n+1+btn.
   else.
   compute btn = 1.
   compute lpmax = 1.
end if.
compute blowp = trunc(lowalp*btn).
do if (blowp < 1).
  compute blowp = 1.
end if.
compute bhighp = trunc((upalp*btn)+1).
do if (bhighp > btn).
  compute bhighp = btn.
end if.
compute indeff = make(n+1+btn,nv-1-nc,-9999).
compute bdbp = 0.
loop #d = 1 to lpmax.
   do if (#d = (n+2)).
    compute dat = dat2.
    compute con = make(n,1,1).
  end if.
  do if (#d > 1 and #d < (n+2)).
    do if (#d = 2).
      compute con = make((n-1),1,1).
      compute dat = dat2(2:n,:).
    else if (#d = (n+1)).
      compute dat = dat2(1:(n-1),:).
    else.
      compute dat = {dat2(1:(#d-2),:);dat2((#d:n),:)}.
    end if.
  end if.
  do if (#d > (n+1)).
    loop.
    compute v=trunc(uniform(n,1)*n)+1.
    compute dat(:,1:nv) = dat2(v,1:nv).
    compute dat3 = {con,dat(:,2:ncol(dat))}.
    compute rk = (rank(dat3)=ncol(dat3)).
    compute bdbp = bdbp+(1-rk).
    end loop if (rk = 1).
  end if.
  compute x = dat(:,2).
  compute m = dat(:,3:(nv-nc)).
  compute y = dat(:,1).
  compute xz = dat(:,2:nv).
  compute xo = {con,x}.
  do if (nc > 0).
    compute c = dat(:,(nv-nc+1):nv).
    compute xo = {xo, c}.
  end if.
  loop #k = 3 to (nv-nc).
     compute ytmp = dat(:,#k).
     compute bzxt = inv(t(xo)*xo)*t(xo)*ytmp.
     compute bzx((#k-2),1)=bzxt(2,1).
     do if (#d = 1).
       compute resid(:,#k-1) = ytmp-(xo*bzxt).
       compute mse=csum((ytmp-(xo*bzxt))&**2)/(n-2-nc).
       compute olscm=(mse*inv((t(xo)*xo))).
       compute bzxse((#k-2),1)=sqrt(olscm(2,2)).
     end if.
  end loop.
  do if (#d = 1).
    do if (nc > 0).
      compute cnt = dd(:,(nv-(nc-1)):nv)).
      compute xo = {con,x,cnt}.
    else.
      compute xo = {con,x}.
    end if.
   do if (ovals = 2).
   compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
   compute pt1 = make(nrow(y),1,0.5).
   compute bt1 = make(ncol(xo),1,0).
   compute LL1 = 0.
   loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byx = bt1+inv(t(xo)*vt1*xo)*t(xo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xo*byx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xo)*vt1*xo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byx.
    compute LL1 = LL2.
    end loop.
    compute byx = byx(2,1).
    compute byxse = sqrt(olscm(2,1)).
    do if (jjj > !iterate).
     compute itprob = 2.
    end if.
  end if.
    do if (ovals <> 2).
    compute byx = inv(t(xo)*xo)*t(xo)*y.
    compute mse=csum((y-(xo*byx))&**2)/(n-2-nc).
    compute olscm=(mse*inv((t(xo)*xo))).
    compute byxse = sqrt(olscm(2,2)).
    compute byx = byx(2,1).
    end if.
  end if.
  compute xzo = {con,xz}.
do if (ovals = 2).
compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
compute LL3 = y&*ln(pt2)+(1-y)&*ln(1-pt2).
compute LL3 = -2*csum(LL3).
compute pt1 = make(nrow(y),1,0.5).
  compute bt1 = make(ncol(xzo),1,0).
  compute LL1 = 0.
  loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byzx = bt1+inv(t(xzo)*vt1*xzo)*t(xzo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xzo*byzx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xzo)*vt1*xzo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byzx.
    compute LL1 = LL2.
  end loop.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    do if (#d = 1).
    compute pi = (exp(xzo*byzx)/(1+exp(xzo*byzx))).
    compute resid(:,ncol(resid))=((y-pt1)/abs(y-pt1))&*sqrt(-2*(LL)).
    end if.
do if (jjj > !iterate).
   compute itprob = 2.
end if.
end if.
  do if (ovals <> 2).
  compute byzx = inv(t(xzo)*xzo)*t(xzo)*y.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (#d = 1).
    compute mse=csum((y-(xzo*byzx))&**2)/(n-nv).
    compute resid(:,ncol(resid))=y-(xzo*byzx).
    compute covmat=mse*inv(t(xzo)*xzo).
    compute olscm=diag(covmat).
    compute sse = mse*(n-nv).
    compute sst = csum((y-(csum(y)/n))&**2).
    compute r2 = 1-(sse/sst).
    compute ar2 = 1-(mse/(sst/(n-1))).
    compute fr = ((n-nv)*r2)/((1-r2)*ncol(xz)).
    compute pfr = 1-fcdf(fr,ncol(xz),(n-nv)).
    do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
  end if.
  end if.
  compute indeff2 = (bzx&*byzx2).
  compute zs = (bzx&/bzxse)&*(byzx2&/byzx2se).
  compute temp = t({csum(indeff2); indeff2}).
  compute indeff(#d,:) = temp.
  do if (#d = 1).
    compute vs = nm(1:(nv-nc),1).
    print/title = "*****************************************************************".
    print/title = "Preacher and Hayes (2008) SPSS Macro for Multiple Mediation".
    print/title = "Written by Andrew F. Hayes, The Ohio State University".
    print/title = "http://www.comm.ohio-state.edu/ahayes/".
    print/title = "For details, see Preacher, K. J., & Hayes, A. F. (2008). Asymptotic".
    print/title = "and resampling strategies for assessing and comparing indirect effects".
    print/title = "in multiple mediator models. Behavior Research Methods, 40, 879-891.".
    print/title = "*****************************************************************".
    print vs/title = "Dependent, Independent, and Proposed Mediator Variables:"/rlabels = "DV =" "IV = " "MEDS = "/format a8.
    do if (nc > 0).
      compute vs = nm((nv-nc+1):nv,1).
      print vs/title = "Statistical Controls:"/rlabels = "CONTROL="/format a8.
    end if.
    print n/title = "Sample size"/format F10.0.
    do if (ovals = 2).
    compute nmsd = {outv, "Analysis"}.
    print rcd/title = "Coding of binary DV for analysis:"/cnames = nmsd/format = F9.2.
    end if.
    compute nms = nm(3:(nv-nc),1).
    compute te = bzx&/bzxse.
    compute df = n-2-nc.
    compute p = 2*(1-tcdf(abs(te), df)).
    compute bzxmat = {bzx, bzxse,te,p}.
    compute b(2:(nv-1-nc),1)=bzx.
    compute se2 = bzxse&*bzxse.
    print bzxmat/title = "IV to Mediators (a paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    compute te = byzx2&/byzx2se.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byzx2mat={byzx2, byzx2se, te, p}.
    print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute byzx2mat={byzx2, byzx2se, te, p, Wald}.
      print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = byx&/byxse.
    compute df = n-2-nc.
    compute xnm = nm(2,1).
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byxmat = {byx, byxse, te, p}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute byxmat = {byx, byxse, te, p, Wald}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = cprime&/cprimese.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute cprimmat = {cprime, cprimese, te, p}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute cprimmat = {cprime, cprimese, te, p, Wald}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    do if (nc > 0).
      compute df = n-nv.
      compute nms = nm((nv-nc+1):nv,1).
      compute te = bcon&/bconse.
      do if (ovals <> 2).
      compute p = 2*(1-tcdf(abs(te), df)).
      compute bconmat = {bcon, bconse,te,p}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
      end if.
      do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute bconmat = {bcon, bconse,te,p, Wald}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
      end if.
    end if.
    do if (ovals <> 2).
    compute dvms = {r2, ar2, fr, ncol(xz), (n-nv), pfr}.
    print dvms/title = "Model Summary for DV Model"/clabels "R-sq" "Adj R-sq" "F" "df1" "df2" "p"/format F9.4.
    end if.
   do if (ovals = 2).
   compute LLdiff = LL3-LL2.
   compute mcF = LLdiff/LL3.
   compute cox = 1-exp(-LLdiff/n).
   compute nagel = cox/(1-exp(-(LL3)/n)).
   compute pf = {LL2, LLdiff, mcF, cox, nagel, n}.
   print pf/title = "Logistic Regression Summary for DV Model"/clabels = "-2LL" "Model LL" "McFadden" "CoxSnell" "Nagelkrk" "n"/format F10.4.
   end if.
    do if (!normal <> 0 and nc = 0 and ovals <> 2).
      compute bmat = make((nv-nc),(nv-nc),0).
      compute bmat(2:(nv-nc-1),1) = bzx.
      compute bmat((nv-nc),2:(nv-nc-1))=t(byzx2).
      compute bmat((nv-nc),1) = cprime.
      compute imbinv = inv(ident(ncol(bmat))-bmat).
      compute imbtinv=inv(ident(ncol(bmat))-t(bmat)).
      compute resid(:,1)=x-(csum(x)/(n)).
      compute psi = sscp(resid)/(n).
      compute invpsi = inv(psi).
      compute ibpsiib = imbinv*psi*imbtinv.
      loop ic = 1 to ncol(info).
      loop ic2 = 1 to ncol(info).
      compute info(ic,ic2)=(n-1)*((imbinv(imat(ic2,4),imat(ic,1))*imbinv(imat(ic,2),imat(ic2,3)))+(ibpsiib(imat(ic2,4),imat(ic,2))*invpsi(imat(ic,1),imat(ic2,3)))).
      end loop.
      end loop.
      compute varcov = inv(info).
      compute varcov = varcov(1:(2*(nv-nc-2)),1:(2*(nv-nc-2))).
      compute ses = diag(varcov).
      compute avar = ses(1:nrow(bzxse),1).
      compute bvar = ses((nrow(bzxse)+1):nrow(ses),1).
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute prws=make(((nv-nc-2)*(nv-nc-3)/2),1,0).
        compute prwse=prws.
        compute kk=1.
        loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
        compute vf2 = ((byzx2(ic,1)**2)*varcov(ic,ic))-(2*byzx2(ic,1)*byzx2(ic2,1)*(varcov(ic,ic2))).
        compute vf2=vf2+((byzx2(ic2,1)**2)*varcov(ic2,ic2))+((bzx(ic,1)**2)*(bvar(ic,1))).
        compute vf2=vf2-(2*bzx(ic,1)*bzx(ic2,1)*covmat((2+ic),(2+ic2)))+((bzx(ic2,1)**2)*(bvar(ic2,1))).
        compute cnt = indeff2(ic,1)-indeff2(ic2,1).
        compute prws(kk,1)=cnt.
        compute prwse(kk,1)=sqrt(vf2).
        compute kk=kk+1.
        end loop.
        end loop.
        compute cnam2 = cname(1:(kk-1),1).
      end if.
      compute dermat = {byzx2;bzx}.
      compute totse = sqrt(t(dermat)*varcov*dermat).
      compute specse = sqrt((byzx2&*byzx2)&*(avar)+(bzx&*bzx)&*(bvar)).
      compute specse = {totse; specse}.
      compute specz = {csum(indeff2);indeff2}&/specse.
      compute ind22 = {csum(indeff2);indeff2}.
      compute nms = {"TOTAL";nm(3:(nv-nc),1)}.
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute ind22 = {ind22;prws}.
        compute specse = {specse;prwse}.
        compute specz = {specz;(prws&/prwse)}.
        compute nms = {nms;cnam2}.
      end if.
      compute pspec= 2*(1-cdfnorm(abs(specz))).
      compute spec = {ind22, specse, specz, pspec}.
      print/title = "******************************************************************".
      print/title = "           NORMAL THEORY TESTS FOR INDIRECT EFFECTS".
      print spec/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Effect" "se" "Z" "p"/format = f9.4.
    end if.
  end if.
end loop.
RELEASE dd, dat, dat2, x, y, m, imat, resid.
do if (btn > 1).
  compute nms = {"TOTAL"; nm(3:(nv-nc),1)}.
  do if ((nv-nc-2) > 1 and (!contrast = 1)).
    compute crst = make((n+1+btn),((nv-nc-2)*(nv-nc-3)/2),0).
    compute kk=1.
    loop ic = 2 to (nv-nc-2).
      loop ic2 = (ic+1) to (nv-nc-1).
        compute crst(:,kk)=indeff(:,ic)-indeff(:,ic2).
        compute kk=kk+1.
      end loop.
    end loop.
    compute indeff = {indeff,crst}.
    compute cnam2 = cname(1:(kk-1),1).
    compute nms = {nms;cnam2}.
  end if.
compute lvout = indeff(2:(n+1),:).
compute tdotm = csum(lvout)/n.
compute tm = (make(n,ncol(lvout),1))*mdiag(tdotm).
compute topa = csum((((n-1)/n)*(tm-lvout))&**3).
compute bota = 6*sqrt((csum((((n-1)/n)*(tm-lvout))&**2)&**3)).
compute ahat = topa&/bota.
compute indsam = t(indeff(1,:)).
compute boot = indeff((n+2):nrow(indeff),:).
compute mnboot = t(csum(boot)/btn).
compute se = (sqrt(((btn*cssq(boot))-(csum(boot)&**2))/((btn-1)*btn))).
loop #e = 1 to ncol(indeff).
  compute boottmp = boot(:,#e).
  compute boottmp(GRADE(boot(:,#e))) = boot(:,#e).
  compute boot(:,#e) = boottmp.
end loop.
compute xp = make((nrow(mnboot)+2),1,0).
loop i = 1 to (nrow(mnboot)+2).
  do if (i <= nrow(mnboot)).
    compute pv = (boot(:,i) < indsam(i,1)).
    compute pv = csum(pv)/btn.
  else.
    compute pv = zbca((i-nrow(mnboot)),1).
  end if.
  compute p = pv.
  do if (pv > .5).
    compute p = 1-pv.
  end if.
  compute y5=sqrt(-2*ln(p)).
  compute xp(i,1)=y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0).
  do if (pv <= .5).
    compute xp(i,1) = -xp(i,1).
  end if.
end loop.
compute bbb = nrow(mnboot).
compute zz = xp(1:bbb,1).
compute zlo = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zup = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute ahat = 0.
compute zlobc = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zupbc = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute zlo = cdfnorm(zlo).
compute zup = cdfnorm(zup).
compute zlobc = cdfnorm(zlobc).
compute zupbc = cdfnorm(zupbc).
compute blow = trunc(zlo*(btn+1)).
compute bhigh = trunc(zup*(btn+1))+1.
compute blowbc = trunc(zlobc*(btn+1)).
compute bhighbc = trunc(zupbc*(btn+1))+1.
compute lowbca = make(nrow(blow),1,0).
compute upbca = lowbca.
loop i = 1 to nrow(blow).
  do if (blow(i,1) < 1).
    compute blow(i,1) = 1.
  end if.
  compute lowbca(i,1)=boot(blow(i,1),i).
  do if (bhigh(i,1) > btn).
    compute bhigh(i,1) = btn.
  end if.
  compute upbca(i,1)=boot(bhigh(i,1),i).
end loop.
compute lowbc = make(nrow(blow),1,0).
compute upbc = lowbca.
loop i = 1 to nrow(blowbc).
  do if (blowbc(i,1) < 1).
    compute blowbc(i,1) = 1.
  end if.
  compute lowbc(i,1)=boot(blowbc(i,1),i).
  do if (bhighbc(i,1) > btn).
    compute bhighbc(i,1) = btn.
  end if.
  compute upbc(i,1)=boot(bhighbc(i,1),i).
end loop.
print/title = "*****************************************************************".
print/title = "           BOOTSTRAP RESULTS FOR INDIRECT EFFECTS".
compute res = {indsam, mnboot,(mnboot-indsam), t(se)}.
print res/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Data" "Boot" "Bias" "SE"/format f9.4.
compute lowperc = boot(blowp,:).
compute upperc = boot(bhighp,:).
compute ci = {lowbca, upbca}.
do if (!bca <> 0).
  print ci/title = "Bias Corrected and Accelerated Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!bc <> 0).
  compute ci = {lowbc, upbc}.
  print ci/title = "Bias Corrected Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!percent <> 0).
  compute ci = {t(lowperc), t(upperc)}.
  print ci/title = "Percentile Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
print/title = "*****************************************************************".
print conf/title = "Level of Confidence for Confidence Intervals:".
print btn/title = "Number of Bootstrap Resamples:".
end if.
do if ((nv-nc-2) > 1 and (!contrast = 1) and ((!normal = 1 and nc = 0) OR btn > 999))).
print/title = "*****************************************************************".
print/title = "  INDIRECT EFFECT CONTRAST DEFINITIONS: Ind_Eff1 MINUS Ind_Eff2".
compute kk=1.
compute prwsv=make(((nv-nc-2)*(nv-nc-3)/2),2,0).
 loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
          compute prwsv(kk,1)=nm(ic+2,1).
          compute prwsv(kk,2)=nm(ic2+2,1).
          compute kk=kk+1.
       end loop.
end loop.
compute prwsv = {cnam2, prwsv}.
print prwsv/title = " "/clabels = "Contrast" "IndEff_1" "IndEff_2"/format A9.
end if.
Print/title = "********************************* NOTES **********************************".
do if (btn = 1 or !normal=1).
Print/title = "Bootstrap confidence intervals are preferred to normal theory tests for".
print/title = "inference about indirect effects.  See Hayes, A. F. (2009). Beyond Baron"/space=0.
print/title =  "and Kenny: Statistical mediation analysis in the new millennium."/space=0.
Print/title = "Communication Monographs, 76, 408-420, or Hayes, A. F. (2013). Introduction to"/space=0.
print/title = "mediation, moderation, and conditional process analysis: A regression-based"/space=0.
print/title = "approach. New York: The Guilford Press"/space=0.
end if.
do if (bdbp > 0).
print/title = "*****************************************************************".
print/title = "WARNING: SOME BOOTSTRAP MATRICES WERE SINGULAR".
print/title = "SINGULAR MATRICES WERE REPLACED DURING RESAMPLING".
print bdbp/title = "Number of singular bootstrap samples replaced:".
end if.
   do if (ovals = 2).
   print/title = "*****************************************************************".
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE FOR MODELS WITH DICHOTOMOUS OUTCOMES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
   do if (nc > 0 and !normal = 1).
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE IN MODELS WITH COVARIATES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
END MATRIX.
RESTORE.
!ENDDEFINE.
INDIRECT y = AngerIngroupFRDiv100/x = PartyInd/m = NationBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 
partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded AngerOutgroupFRDiv100/boot = 10000/conf = 95/normal = 0/contrast = 0/percent = 0/bc = 0/bca = 1.

/* Written by Andrew F. Hayes */.
/* http://www.afhayes.com */.
/* Version 4.2 */.
DEFINE INDIRECT (y = !charend('/')/x = !charend('/')/m = !charend('/')/c=!charend('/') !default(xxxxx)/
  boot =!charend('/') !default(1000)/conf = !charend('/') !default(95)/percent = !charend('/') !default(0)/bc = !charend('/')
  !default(1)/bca = !charend('/') !default(0)/normal = !charend ('/') !default(0)/contrast = !charend ('/') !default(0)/iterate = !charend('/') !default(10000)/converge =
  !charend('/') !default(.0000001)).
PRESERVE.
SET LENGTH = NONE.
SET MXLOOPS = 10000001.
SET SEED = RANDOM.
SET PRINTBACK = OFF.
MATRIX.
get dd/variables = !y !x !m/names = nm/MISSING = OMIT.
compute temp = ncol(dd).
get dd2/variables = !y !x NationBenefitsDiv100/MISSING = OMIT.
compute nc = ncol(dd)-ncol(dd2).
compute ovals = ncol(design(dd(:,1))).
do if (ovals = 2).
   compute omx = cmax(dd(:,1)).
   compute omn = cmin(dd(:,1)).
   compute dd(:,1) = (dd(:,1) = omx).
   compute rcd = {omn, 0; omx, 1}.
end if.
compute nm = t(nm).
compute outv = t(nm(1,1)).
compute n = nrow(dd).
compute nv = ncol(dd).
compute con = make(n,1,1).
compute dat2 = dd.
compute dat = dd.
compute bzx = make(nv-2-nc,1,0).
compute bzxse = make(nv-2-nc,1,0).
compute b=make((nv-1-nc),(nv-1-nc),0).
compute resid = make(n,(nv-nc),0).
compute info = make((2*(nv-nc-2)+1),(2*(nv-nc-2)+1),0).
compute imat = make(ncol(info),4,1).
compute imat(1:(nv-nc-2),1)=t({2:(nv-nc-1):1}).
compute imat(1:(nv-nc-2),3)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),2)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),4)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),1)=make((nv-nc-2),1,(nv-nc)).
compute imat((nv-nc-1):(ncol(info)-1),3)=make((nv-nc-2),1,(nv-nc)).
compute imat(ncol(info),:)={(nv-nc),1,(nv-nc),1}.
compute cname={"C1";"C2";"C3";"C4";"C5";"C6";"C7";"C8";"C9";"C10";"C11";"C12";"C13";"C14";"C15";"C16";"C17"}.
compute cname={cname;"C18";"C19";"C20";"C21";"C22";"C23";"C24";"C25";"C26";"C27";"C28";"C29";"C30";"C31"}.
compute cname={cname;"C32";"C33";"C34";"C35";"C36";"C37";"C38";"C39";"C40";"C41";"C42";"C43";"C44";"C45"}.
compute p0=-.322232431088.
compute p1 = -1.
compute p2 = -.342242088547.
compute p3 = -.0204231210245.
compute p4 = -.0000453642210148.
compute q0 = .0993484626060.
compute q1 = .588581570495.
compute q2 = .531103462366.
compute q3 = .103537752850.
compute q4 = .0038560700634.
compute conf = rnd(!conf).
compute lowalp = 0.5*(1-(conf/100)).
compute upalp = 0.5*(1+(conf/100)).
compute zbca = {lowalp; upalp}.
do if (!boot > 999).
   compute btn = trunc(!boot/1000)*1000.
   compute lpmax = n+1+btn.
   else.
   compute btn = 1.
   compute lpmax = 1.
end if.
compute blowp = trunc(lowalp*btn).
do if (blowp < 1).
  compute blowp = 1.
end if.
compute bhighp = trunc((upalp*btn)+1).
do if (bhighp > btn).
  compute bhighp = btn.
end if.
compute indeff = make(n+1+btn,nv-1-nc,-9999).
compute bdbp = 0.
loop #d = 1 to lpmax.
   do if (#d = (n+2)).
    compute dat = dat2.
    compute con = make(n,1,1).
  end if.
  do if (#d > 1 and #d < (n+2)).
    do if (#d = 2).
      compute con = make((n-1),1,1).
      compute dat = dat2(2:n,:).
    else if (#d = (n+1)).
      compute dat = dat2(1:(n-1),:).
    else.
      compute dat = {dat2(1:(#d-2),:);dat2((#d:n),:)}.
    end if.
  end if.
  do if (#d > (n+1)).
    loop.
    compute v=trunc(uniform(n,1)*n)+1.
    compute dat(:,1:nv) = dat2(v,1:nv).
    compute dat3 = {con,dat(:,2:ncol(dat))}.
    compute rk = (rank(dat3)=ncol(dat3)).
    compute bdbp = bdbp+(1-rk).
    end loop if (rk = 1).
  end if.
  compute x = dat(:,2).
  compute m = dat(:,3:(nv-nc)).
  compute y = dat(:,1).
  compute xz = dat(:,2:nv).
  compute xo = {con,x}.
  do if (nc > 0).
    compute c = dat(:,(nv-nc+1):nv).
    compute xo = {xo, c}.
  end if.
  loop #k = 3 to (nv-nc).
     compute ytmp = dat(:,#k).
     compute bzxt = inv(t(xo)*xo)*t(xo)*ytmp.
     compute bzx((#k-2),1)=bzxt(2,1).
     do if (#d = 1).
       compute resid(:,#k-1) = ytmp-(xo*bzxt).
       compute mse=csum((ytmp-(xo*bzxt))&**2)/(n-2-nc).
       compute olscm=(mse*inv((t(xo)*xo))).
       compute bzxse((#k-2),1)=sqrt(olscm(2,2)).
     end if.
  end loop.
  do if (#d = 1).
    do if (nc > 0).
      compute cnt = dd(:,(nv-(nc-1)):nv)).
      compute xo = {con,x,cnt}.
    else.
      compute xo = {con,x}.
    end if.
   do if (ovals = 2).
   compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
   compute pt1 = make(nrow(y),1,0.5).
   compute bt1 = make(ncol(xo),1,0).
   compute LL1 = 0.
   loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byx = bt1+inv(t(xo)*vt1*xo)*t(xo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xo*byx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xo)*vt1*xo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byx.
    compute LL1 = LL2.
    end loop.
    compute byx = byx(2,1).
    compute byxse = sqrt(olscm(2,1)).
    do if (jjj > !iterate).
     compute itprob = 2.
    end if.
  end if.
    do if (ovals <> 2).
    compute byx = inv(t(xo)*xo)*t(xo)*y.
    compute mse=csum((y-(xo*byx))&**2)/(n-2-nc).
    compute olscm=(mse*inv((t(xo)*xo))).
    compute byxse = sqrt(olscm(2,2)).
    compute byx = byx(2,1).
    end if.
  end if.
  compute xzo = {con,xz}.
do if (ovals = 2).
compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
compute LL3 = y&*ln(pt2)+(1-y)&*ln(1-pt2).
compute LL3 = -2*csum(LL3).
compute pt1 = make(nrow(y),1,0.5).
  compute bt1 = make(ncol(xzo),1,0).
  compute LL1 = 0.
  loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byzx = bt1+inv(t(xzo)*vt1*xzo)*t(xzo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xzo*byzx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xzo)*vt1*xzo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byzx.
    compute LL1 = LL2.
  end loop.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    do if (#d = 1).
    compute pi = (exp(xzo*byzx)/(1+exp(xzo*byzx))).
    compute resid(:,ncol(resid))=((y-pt1)/abs(y-pt1))&*sqrt(-2*(LL)).
    end if.
do if (jjj > !iterate).
   compute itprob = 2.
end if.
end if.
  do if (ovals <> 2).
  compute byzx = inv(t(xzo)*xzo)*t(xzo)*y.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (#d = 1).
    compute mse=csum((y-(xzo*byzx))&**2)/(n-nv).
    compute resid(:,ncol(resid))=y-(xzo*byzx).
    compute covmat=mse*inv(t(xzo)*xzo).
    compute olscm=diag(covmat).
    compute sse = mse*(n-nv).
    compute sst = csum((y-(csum(y)/n))&**2).
    compute r2 = 1-(sse/sst).
    compute ar2 = 1-(mse/(sst/(n-1))).
    compute fr = ((n-nv)*r2)/((1-r2)*ncol(xz)).
    compute pfr = 1-fcdf(fr,ncol(xz),(n-nv)).
    do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
  end if.
  end if.
  compute indeff2 = (bzx&*byzx2).
  compute zs = (bzx&/bzxse)&*(byzx2&/byzx2se).
  compute temp = t({csum(indeff2); indeff2}).
  compute indeff(#d,:) = temp.
  do if (#d = 1).
    compute vs = nm(1:(nv-nc),1).
    print/title = "*****************************************************************".
    print/title = "Preacher and Hayes (2008) SPSS Macro for Multiple Mediation".
    print/title = "Written by Andrew F. Hayes, The Ohio State University".
    print/title = "http://www.comm.ohio-state.edu/ahayes/".
    print/title = "For details, see Preacher, K. J., & Hayes, A. F. (2008). Asymptotic".
    print/title = "and resampling strategies for assessing and comparing indirect effects".
    print/title = "in multiple mediator models. Behavior Research Methods, 40, 879-891.".
    print/title = "*****************************************************************".
    print vs/title = "Dependent, Independent, and Proposed Mediator Variables:"/rlabels = "DV =" "IV = " "MEDS = "/format a8.
    do if (nc > 0).
      compute vs = nm((nv-nc+1):nv,1).
      print vs/title = "Statistical Controls:"/rlabels = "CONTROL="/format a8.
    end if.
    print n/title = "Sample size"/format F10.0.
    do if (ovals = 2).
    compute nmsd = {outv, "Analysis"}.
    print rcd/title = "Coding of binary DV for analysis:"/cnames = nmsd/format = F9.2.
    end if.
    compute nms = nm(3:(nv-nc),1).
    compute te = bzx&/bzxse.
    compute df = n-2-nc.
    compute p = 2*(1-tcdf(abs(te), df)).
    compute bzxmat = {bzx, bzxse,te,p}.
    compute b(2:(nv-1-nc),1)=bzx.
    compute se2 = bzxse&*bzxse.
    print bzxmat/title = "IV to Mediators (a paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    compute te = byzx2&/byzx2se.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byzx2mat={byzx2, byzx2se, te, p}.
    print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute byzx2mat={byzx2, byzx2se, te, p, Wald}.
      print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = byx&/byxse.
    compute df = n-2-nc.
    compute xnm = nm(2,1).
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byxmat = {byx, byxse, te, p}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute byxmat = {byx, byxse, te, p, Wald}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = cprime&/cprimese.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute cprimmat = {cprime, cprimese, te, p}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute cprimmat = {cprime, cprimese, te, p, Wald}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    do if (nc > 0).
      compute df = n-nv.
      compute nms = nm((nv-nc+1):nv,1).
      compute te = bcon&/bconse.
      do if (ovals <> 2).
      compute p = 2*(1-tcdf(abs(te), df)).
      compute bconmat = {bcon, bconse,te,p}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
      end if.
      do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute bconmat = {bcon, bconse,te,p, Wald}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
      end if.
    end if.
    do if (ovals <> 2).
    compute dvms = {r2, ar2, fr, ncol(xz), (n-nv), pfr}.
    print dvms/title = "Model Summary for DV Model"/clabels "R-sq" "Adj R-sq" "F" "df1" "df2" "p"/format F9.4.
    end if.
   do if (ovals = 2).
   compute LLdiff = LL3-LL2.
   compute mcF = LLdiff/LL3.
   compute cox = 1-exp(-LLdiff/n).
   compute nagel = cox/(1-exp(-(LL3)/n)).
   compute pf = {LL2, LLdiff, mcF, cox, nagel, n}.
   print pf/title = "Logistic Regression Summary for DV Model"/clabels = "-2LL" "Model LL" "McFadden" "CoxSnell" "Nagelkrk" "n"/format F10.4.
   end if.
    do if (!normal <> 0 and nc = 0 and ovals <> 2).
      compute bmat = make((nv-nc),(nv-nc),0).
      compute bmat(2:(nv-nc-1),1) = bzx.
      compute bmat((nv-nc),2:(nv-nc-1))=t(byzx2).
      compute bmat((nv-nc),1) = cprime.
      compute imbinv = inv(ident(ncol(bmat))-bmat).
      compute imbtinv=inv(ident(ncol(bmat))-t(bmat)).
      compute resid(:,1)=x-(csum(x)/(n)).
      compute psi = sscp(resid)/(n).
      compute invpsi = inv(psi).
      compute ibpsiib = imbinv*psi*imbtinv.
      loop ic = 1 to ncol(info).
      loop ic2 = 1 to ncol(info).
      compute info(ic,ic2)=(n-1)*((imbinv(imat(ic2,4),imat(ic,1))*imbinv(imat(ic,2),imat(ic2,3)))+(ibpsiib(imat(ic2,4),imat(ic,2))*invpsi(imat(ic,1),imat(ic2,3)))).
      end loop.
      end loop.
      compute varcov = inv(info).
      compute varcov = varcov(1:(2*(nv-nc-2)),1:(2*(nv-nc-2))).
      compute ses = diag(varcov).
      compute avar = ses(1:nrow(bzxse),1).
      compute bvar = ses((nrow(bzxse)+1):nrow(ses),1).
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute prws=make(((nv-nc-2)*(nv-nc-3)/2),1,0).
        compute prwse=prws.
        compute kk=1.
        loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
        compute vf2 = ((byzx2(ic,1)**2)*varcov(ic,ic))-(2*byzx2(ic,1)*byzx2(ic2,1)*(varcov(ic,ic2))).
        compute vf2=vf2+((byzx2(ic2,1)**2)*varcov(ic2,ic2))+((bzx(ic,1)**2)*(bvar(ic,1))).
        compute vf2=vf2-(2*bzx(ic,1)*bzx(ic2,1)*covmat((2+ic),(2+ic2)))+((bzx(ic2,1)**2)*(bvar(ic2,1))).
        compute cnt = indeff2(ic,1)-indeff2(ic2,1).
        compute prws(kk,1)=cnt.
        compute prwse(kk,1)=sqrt(vf2).
        compute kk=kk+1.
        end loop.
        end loop.
        compute cnam2 = cname(1:(kk-1),1).
      end if.
      compute dermat = {byzx2;bzx}.
      compute totse = sqrt(t(dermat)*varcov*dermat).
      compute specse = sqrt((byzx2&*byzx2)&*(avar)+(bzx&*bzx)&*(bvar)).
      compute specse = {totse; specse}.
      compute specz = {csum(indeff2);indeff2}&/specse.
      compute ind22 = {csum(indeff2);indeff2}.
      compute nms = {"TOTAL";nm(3:(nv-nc),1)}.
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute ind22 = {ind22;prws}.
        compute specse = {specse;prwse}.
        compute specz = {specz;(prws&/prwse)}.
        compute nms = {nms;cnam2}.
      end if.
      compute pspec= 2*(1-cdfnorm(abs(specz))).
      compute spec = {ind22, specse, specz, pspec}.
      print/title = "******************************************************************".
      print/title = "           NORMAL THEORY TESTS FOR INDIRECT EFFECTS".
      print spec/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Effect" "se" "Z" "p"/format = f9.4.
    end if.
  end if.
end loop.
RELEASE dd, dat, dat2, x, y, m, imat, resid.
do if (btn > 1).
  compute nms = {"TOTAL"; nm(3:(nv-nc),1)}.
  do if ((nv-nc-2) > 1 and (!contrast = 1)).
    compute crst = make((n+1+btn),((nv-nc-2)*(nv-nc-3)/2),0).
    compute kk=1.
    loop ic = 2 to (nv-nc-2).
      loop ic2 = (ic+1) to (nv-nc-1).
        compute crst(:,kk)=indeff(:,ic)-indeff(:,ic2).
        compute kk=kk+1.
      end loop.
    end loop.
    compute indeff = {indeff,crst}.
    compute cnam2 = cname(1:(kk-1),1).
    compute nms = {nms;cnam2}.
  end if.
compute lvout = indeff(2:(n+1),:).
compute tdotm = csum(lvout)/n.
compute tm = (make(n,ncol(lvout),1))*mdiag(tdotm).
compute topa = csum((((n-1)/n)*(tm-lvout))&**3).
compute bota = 6*sqrt((csum((((n-1)/n)*(tm-lvout))&**2)&**3)).
compute ahat = topa&/bota.
compute indsam = t(indeff(1,:)).
compute boot = indeff((n+2):nrow(indeff),:).
compute mnboot = t(csum(boot)/btn).
compute se = (sqrt(((btn*cssq(boot))-(csum(boot)&**2))/((btn-1)*btn))).
loop #e = 1 to ncol(indeff).
  compute boottmp = boot(:,#e).
  compute boottmp(GRADE(boot(:,#e))) = boot(:,#e).
  compute boot(:,#e) = boottmp.
end loop.
compute xp = make((nrow(mnboot)+2),1,0).
loop i = 1 to (nrow(mnboot)+2).
  do if (i <= nrow(mnboot)).
    compute pv = (boot(:,i) < indsam(i,1)).
    compute pv = csum(pv)/btn.
  else.
    compute pv = zbca((i-nrow(mnboot)),1).
  end if.
  compute p = pv.
  do if (pv > .5).
    compute p = 1-pv.
  end if.
  compute y5=sqrt(-2*ln(p)).
  compute xp(i,1)=y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0).
  do if (pv <= .5).
    compute xp(i,1) = -xp(i,1).
  end if.
end loop.
compute bbb = nrow(mnboot).
compute zz = xp(1:bbb,1).
compute zlo = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zup = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute ahat = 0.
compute zlobc = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zupbc = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute zlo = cdfnorm(zlo).
compute zup = cdfnorm(zup).
compute zlobc = cdfnorm(zlobc).
compute zupbc = cdfnorm(zupbc).
compute blow = trunc(zlo*(btn+1)).
compute bhigh = trunc(zup*(btn+1))+1.
compute blowbc = trunc(zlobc*(btn+1)).
compute bhighbc = trunc(zupbc*(btn+1))+1.
compute lowbca = make(nrow(blow),1,0).
compute upbca = lowbca.
loop i = 1 to nrow(blow).
  do if (blow(i,1) < 1).
    compute blow(i,1) = 1.
  end if.
  compute lowbca(i,1)=boot(blow(i,1),i).
  do if (bhigh(i,1) > btn).
    compute bhigh(i,1) = btn.
  end if.
  compute upbca(i,1)=boot(bhigh(i,1),i).
end loop.
compute lowbc = make(nrow(blow),1,0).
compute upbc = lowbca.
loop i = 1 to nrow(blowbc).
  do if (blowbc(i,1) < 1).
    compute blowbc(i,1) = 1.
  end if.
  compute lowbc(i,1)=boot(blowbc(i,1),i).
  do if (bhighbc(i,1) > btn).
    compute bhighbc(i,1) = btn.
  end if.
  compute upbc(i,1)=boot(bhighbc(i,1),i).
end loop.
print/title = "*****************************************************************".
print/title = "           BOOTSTRAP RESULTS FOR INDIRECT EFFECTS".
compute res = {indsam, mnboot,(mnboot-indsam), t(se)}.
print res/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Data" "Boot" "Bias" "SE"/format f9.4.
compute lowperc = boot(blowp,:).
compute upperc = boot(bhighp,:).
compute ci = {lowbca, upbca}.
do if (!bca <> 0).
  print ci/title = "Bias Corrected and Accelerated Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!bc <> 0).
  compute ci = {lowbc, upbc}.
  print ci/title = "Bias Corrected Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!percent <> 0).
  compute ci = {t(lowperc), t(upperc)}.
  print ci/title = "Percentile Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
print/title = "*****************************************************************".
print conf/title = "Level of Confidence for Confidence Intervals:".
print btn/title = "Number of Bootstrap Resamples:".
end if.
do if ((nv-nc-2) > 1 and (!contrast = 1) and ((!normal = 1 and nc = 0) OR btn > 999))).
print/title = "*****************************************************************".
print/title = "  INDIRECT EFFECT CONTRAST DEFINITIONS: Ind_Eff1 MINUS Ind_Eff2".
compute kk=1.
compute prwsv=make(((nv-nc-2)*(nv-nc-3)/2),2,0).
 loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
          compute prwsv(kk,1)=nm(ic+2,1).
          compute prwsv(kk,2)=nm(ic2+2,1).
          compute kk=kk+1.
       end loop.
end loop.
compute prwsv = {cnam2, prwsv}.
print prwsv/title = " "/clabels = "Contrast" "IndEff_1" "IndEff_2"/format A9.
end if.
Print/title = "********************************* NOTES **********************************".
do if (btn = 1 or !normal=1).
Print/title = "Bootstrap confidence intervals are preferred to normal theory tests for".
print/title = "inference about indirect effects.  See Hayes, A. F. (2009). Beyond Baron"/space=0.
print/title =  "and Kenny: Statistical mediation analysis in the new millennium."/space=0.
Print/title = "Communication Monographs, 76, 408-420, or Hayes, A. F. (2013). Introduction to"/space=0.
print/title = "mediation, moderation, and conditional process analysis: A regression-based"/space=0.
print/title = "approach. New York: The Guilford Press"/space=0.
end if.
do if (bdbp > 0).
print/title = "*****************************************************************".
print/title = "WARNING: SOME BOOTSTRAP MATRICES WERE SINGULAR".
print/title = "SINGULAR MATRICES WERE REPLACED DURING RESAMPLING".
print bdbp/title = "Number of singular bootstrap samples replaced:".
end if.
   do if (ovals = 2).
   print/title = "*****************************************************************".
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE FOR MODELS WITH DICHOTOMOUS OUTCOMES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
   do if (nc > 0 and !normal = 1).
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE IN MODELS WITH COVARIATES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
END MATRIX.
RESTORE.
!ENDDEFINE.
INDIRECT y = GratIngroupConDiv100/x = PartyInd/m = NationBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 PersBenefitsDiv100 
partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded GratOutgroupConDiv100/boot = 10000/conf = 95/normal = 0/contrast = 0/percent = 0/bc = 0/bca = 1.


/* Written by Andrew F. Hayes */.
/* http://www.afhayes.com */.
/* Version 4.2 */.
DEFINE INDIRECT (y = !charend('/')/x = !charend('/')/m = !charend('/')/c=!charend('/') !default(xxxxx)/
  boot =!charend('/') !default(1000)/conf = !charend('/') !default(95)/percent = !charend('/') !default(0)/bc = !charend('/')
  !default(1)/bca = !charend('/') !default(0)/normal = !charend ('/') !default(0)/contrast = !charend ('/') !default(0)/iterate = !charend('/') !default(10000)/converge =
  !charend('/') !default(.0000001)).
PRESERVE.
SET LENGTH = NONE.
SET MXLOOPS = 10000001.
SET SEED = RANDOM.
SET PRINTBACK = OFF.
MATRIX.
get dd/variables = !y !x !m/names = nm/MISSING = OMIT.
compute temp = ncol(dd).
get dd2/variables = !y !x PersBenefitsDiv100/MISSING = OMIT.
compute nc = ncol(dd)-ncol(dd2).
compute ovals = ncol(design(dd(:,1))).
do if (ovals = 2).
   compute omx = cmax(dd(:,1)).
   compute omn = cmin(dd(:,1)).
   compute dd(:,1) = (dd(:,1) = omx).
   compute rcd = {omn, 0; omx, 1}.
end if.
compute nm = t(nm).
compute outv = t(nm(1,1)).
compute n = nrow(dd).
compute nv = ncol(dd).
compute con = make(n,1,1).
compute dat2 = dd.
compute dat = dd.
compute bzx = make(nv-2-nc,1,0).
compute bzxse = make(nv-2-nc,1,0).
compute b=make((nv-1-nc),(nv-1-nc),0).
compute resid = make(n,(nv-nc),0).
compute info = make((2*(nv-nc-2)+1),(2*(nv-nc-2)+1),0).
compute imat = make(ncol(info),4,1).
compute imat(1:(nv-nc-2),1)=t({2:(nv-nc-1):1}).
compute imat(1:(nv-nc-2),3)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),2)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),4)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),1)=make((nv-nc-2),1,(nv-nc)).
compute imat((nv-nc-1):(ncol(info)-1),3)=make((nv-nc-2),1,(nv-nc)).
compute imat(ncol(info),:)={(nv-nc),1,(nv-nc),1}.
compute cname={"C1";"C2";"C3";"C4";"C5";"C6";"C7";"C8";"C9";"C10";"C11";"C12";"C13";"C14";"C15";"C16";"C17"}.
compute cname={cname;"C18";"C19";"C20";"C21";"C22";"C23";"C24";"C25";"C26";"C27";"C28";"C29";"C30";"C31"}.
compute cname={cname;"C32";"C33";"C34";"C35";"C36";"C37";"C38";"C39";"C40";"C41";"C42";"C43";"C44";"C45"}.
compute p0=-.322232431088.
compute p1 = -1.
compute p2 = -.342242088547.
compute p3 = -.0204231210245.
compute p4 = -.0000453642210148.
compute q0 = .0993484626060.
compute q1 = .588581570495.
compute q2 = .531103462366.
compute q3 = .103537752850.
compute q4 = .0038560700634.
compute conf = rnd(!conf).
compute lowalp = 0.5*(1-(conf/100)).
compute upalp = 0.5*(1+(conf/100)).
compute zbca = {lowalp; upalp}.
do if (!boot > 999).
   compute btn = trunc(!boot/1000)*1000.
   compute lpmax = n+1+btn.
   else.
   compute btn = 1.
   compute lpmax = 1.
end if.
compute blowp = trunc(lowalp*btn).
do if (blowp < 1).
  compute blowp = 1.
end if.
compute bhighp = trunc((upalp*btn)+1).
do if (bhighp > btn).
  compute bhighp = btn.
end if.
compute indeff = make(n+1+btn,nv-1-nc,-9999).
compute bdbp = 0.
loop #d = 1 to lpmax.
   do if (#d = (n+2)).
    compute dat = dat2.
    compute con = make(n,1,1).
  end if.
  do if (#d > 1 and #d < (n+2)).
    do if (#d = 2).
      compute con = make((n-1),1,1).
      compute dat = dat2(2:n,:).
    else if (#d = (n+1)).
      compute dat = dat2(1:(n-1),:).
    else.
      compute dat = {dat2(1:(#d-2),:);dat2((#d:n),:)}.
    end if.
  end if.
  do if (#d > (n+1)).
    loop.
    compute v=trunc(uniform(n,1)*n)+1.
    compute dat(:,1:nv) = dat2(v,1:nv).
    compute dat3 = {con,dat(:,2:ncol(dat))}.
    compute rk = (rank(dat3)=ncol(dat3)).
    compute bdbp = bdbp+(1-rk).
    end loop if (rk = 1).
  end if.
  compute x = dat(:,2).
  compute m = dat(:,3:(nv-nc)).
  compute y = dat(:,1).
  compute xz = dat(:,2:nv).
  compute xo = {con,x}.
  do if (nc > 0).
    compute c = dat(:,(nv-nc+1):nv).
    compute xo = {xo, c}.
  end if.
  loop #k = 3 to (nv-nc).
     compute ytmp = dat(:,#k).
     compute bzxt = inv(t(xo)*xo)*t(xo)*ytmp.
     compute bzx((#k-2),1)=bzxt(2,1).
     do if (#d = 1).
       compute resid(:,#k-1) = ytmp-(xo*bzxt).
       compute mse=csum((ytmp-(xo*bzxt))&**2)/(n-2-nc).
       compute olscm=(mse*inv((t(xo)*xo))).
       compute bzxse((#k-2),1)=sqrt(olscm(2,2)).
     end if.
  end loop.
  do if (#d = 1).
    do if (nc > 0).
      compute cnt = dd(:,(nv-(nc-1)):nv)).
      compute xo = {con,x,cnt}.
    else.
      compute xo = {con,x}.
    end if.
   do if (ovals = 2).
   compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
   compute pt1 = make(nrow(y),1,0.5).
   compute bt1 = make(ncol(xo),1,0).
   compute LL1 = 0.
   loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byx = bt1+inv(t(xo)*vt1*xo)*t(xo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xo*byx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xo)*vt1*xo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byx.
    compute LL1 = LL2.
    end loop.
    compute byx = byx(2,1).
    compute byxse = sqrt(olscm(2,1)).
    do if (jjj > !iterate).
     compute itprob = 2.
    end if.
  end if.
    do if (ovals <> 2).
    compute byx = inv(t(xo)*xo)*t(xo)*y.
    compute mse=csum((y-(xo*byx))&**2)/(n-2-nc).
    compute olscm=(mse*inv((t(xo)*xo))).
    compute byxse = sqrt(olscm(2,2)).
    compute byx = byx(2,1).
    end if.
  end if.
  compute xzo = {con,xz}.
do if (ovals = 2).
compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
compute LL3 = y&*ln(pt2)+(1-y)&*ln(1-pt2).
compute LL3 = -2*csum(LL3).
compute pt1 = make(nrow(y),1,0.5).
  compute bt1 = make(ncol(xzo),1,0).
  compute LL1 = 0.
  loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byzx = bt1+inv(t(xzo)*vt1*xzo)*t(xzo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xzo*byzx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xzo)*vt1*xzo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byzx.
    compute LL1 = LL2.
  end loop.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    do if (#d = 1).
    compute pi = (exp(xzo*byzx)/(1+exp(xzo*byzx))).
    compute resid(:,ncol(resid))=((y-pt1)/abs(y-pt1))&*sqrt(-2*(LL)).
    end if.
do if (jjj > !iterate).
   compute itprob = 2.
end if.
end if.
  do if (ovals <> 2).
  compute byzx = inv(t(xzo)*xzo)*t(xzo)*y.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (#d = 1).
    compute mse=csum((y-(xzo*byzx))&**2)/(n-nv).
    compute resid(:,ncol(resid))=y-(xzo*byzx).
    compute covmat=mse*inv(t(xzo)*xzo).
    compute olscm=diag(covmat).
    compute sse = mse*(n-nv).
    compute sst = csum((y-(csum(y)/n))&**2).
    compute r2 = 1-(sse/sst).
    compute ar2 = 1-(mse/(sst/(n-1))).
    compute fr = ((n-nv)*r2)/((1-r2)*ncol(xz)).
    compute pfr = 1-fcdf(fr,ncol(xz),(n-nv)).
    do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
  end if.
  end if.
  compute indeff2 = (bzx&*byzx2).
  compute zs = (bzx&/bzxse)&*(byzx2&/byzx2se).
  compute temp = t({csum(indeff2); indeff2}).
  compute indeff(#d,:) = temp.
  do if (#d = 1).
    compute vs = nm(1:(nv-nc),1).
    print/title = "*****************************************************************".
    print/title = "Preacher and Hayes (2008) SPSS Macro for Multiple Mediation"/space=0.
    print/title = "Written by Andrew F. Hayes, The Ohio State University"/space=0.
    print/title = "www.afhayes.com"/space=0.
    print/title = "For details, see Preacher, K. J., & Hayes, A. F. (2008). Asymptotic"/space=0.
    print/title = "and resampling strategies for assessing and comparing indirect effects"/space=0.
    print/title = "in multiple mediator models. Behavior Research Methods, 40, 879-891."/space=0.
    print/title = "Also see Chapter 5 of Introduction to Mediation, Moderation, and Conditional"/space=0.
    print/title = "Analysis.  New York: The Guilford Press.  http://www.guilford.com/p/hayes3"/space=0.
    print/title = "*****************************************************************"/space=0.
    print vs/title = "Dependent, Independent, and Proposed Mediator Variables:"/rlabels = "DV =" "IV = " "MEDS = "/format a8.
    do if (nc > 0).
      compute vs = nm((nv-nc+1):nv,1).
      print vs/title = "Statistical Controls:"/rlabels = "CONTROL="/format a8.
    end if.
    print n/title = "Sample size"/format F10.0.
    do if (ovals = 2).
    compute nmsd = {outv, "Analysis"}.
    print rcd/title = "Coding of binary DV for analysis:"/cnames = nmsd/format = F9.2.
    end if.
    compute nms = nm(3:(nv-nc),1).
    compute te = bzx&/bzxse.
    compute df = n-2-nc.
    compute p = 2*(1-tcdf(abs(te), df)).
    compute bzxmat = {bzx, bzxse,te,p}.
    compute b(2:(nv-1-nc),1)=bzx.
    compute se2 = bzxse&*bzxse.
    print bzxmat/title = "IV to Mediators (a paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    compute te = byzx2&/byzx2se.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byzx2mat={byzx2, byzx2se, te, p}.
    print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute byzx2mat={byzx2, byzx2se, te, p, Wald}.
      print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = byx&/byxse.
    compute df = n-2-nc.
    compute xnm = nm(2,1).
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byxmat = {byx, byxse, te, p}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute byxmat = {byx, byxse, te, p, Wald}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = cprime&/cprimese.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute cprimmat = {cprime, cprimese, te, p}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute cprimmat = {cprime, cprimese, te, p, Wald}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    do if (nc > 0).
      compute df = n-nv.
      compute nms = nm((nv-nc+1):nv,1).
      compute te = bcon&/bconse.
      do if (ovals <> 2).
      compute p = 2*(1-tcdf(abs(te), df)).
      compute bconmat = {bcon, bconse,te,p}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
      end if.
      do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute bconmat = {bcon, bconse,te,p, Wald}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
      end if.
    end if.
    do if (ovals <> 2).
    compute dvms = {r2, ar2, fr, ncol(xz), (n-nv), pfr}.
    print dvms/title = "Model Summary for DV Model"/clabels "R-sq" "Adj R-sq" "F" "df1" "df2" "p"/format F9.4.
    end if.
   do if (ovals = 2).
   compute LLdiff = LL3-LL2.
   compute mcF = LLdiff/LL3.
   compute cox = 1-exp(-LLdiff/n).
   compute nagel = cox/(1-exp(-(LL3)/n)).
   compute pf = {LL2, LLdiff, mcF, cox, nagel, n}.
   print pf/title = "Logistic Regression Summary for DV Model"/clabels = "-2LL" "Model LL" "McFadden" "CoxSnell" "Nagelkrk" "n"/format F10.4.
   end if.
    do if (!normal <> 0 and nc = 0 and ovals <> 2).
      compute bmat = make((nv-nc),(nv-nc),0).
      compute bmat(2:(nv-nc-1),1) = bzx.
      compute bmat((nv-nc),2:(nv-nc-1))=t(byzx2).
      compute bmat((nv-nc),1) = cprime.
      compute imbinv = inv(ident(ncol(bmat))-bmat).
      compute imbtinv=inv(ident(ncol(bmat))-t(bmat)).
      compute resid(:,1)=x-(csum(x)/(n)).
      compute psi = sscp(resid)/(n).
      compute invpsi = inv(psi).
      compute ibpsiib = imbinv*psi*imbtinv.
      loop ic = 1 to ncol(info).
      loop ic2 = 1 to ncol(info).
      compute info(ic,ic2)=(n-1)*((imbinv(imat(ic2,4),imat(ic,1))*imbinv(imat(ic,2),imat(ic2,3)))+(ibpsiib(imat(ic2,4),imat(ic,2))*invpsi(imat(ic,1),imat(ic2,3)))).
      end loop.
      end loop.
      compute varcov = inv(info).
      compute varcov = varcov(1:(2*(nv-nc-2)),1:(2*(nv-nc-2))).
      compute ses = diag(varcov).
      compute avar = ses(1:nrow(bzxse),1).
      compute bvar = ses((nrow(bzxse)+1):nrow(ses),1).
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute prws=make(((nv-nc-2)*(nv-nc-3)/2),1,0).
        compute prwse=prws.
        compute kk=1.
        loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
        compute vf2 = ((byzx2(ic,1)**2)*varcov(ic,ic))-(2*byzx2(ic,1)*byzx2(ic2,1)*(varcov(ic,ic2))).
        compute vf2=vf2+((byzx2(ic2,1)**2)*varcov(ic2,ic2))+((bzx(ic,1)**2)*(bvar(ic,1))).
        compute vf2=vf2-(2*bzx(ic,1)*bzx(ic2,1)*covmat((2+ic),(2+ic2)))+((bzx(ic2,1)**2)*(bvar(ic2,1))).
        compute cnt = indeff2(ic,1)-indeff2(ic2,1).
        compute prws(kk,1)=cnt.
        compute prwse(kk,1)=sqrt(vf2).
        compute kk=kk+1.
        end loop.
        end loop.
        compute cnam2 = cname(1:(kk-1),1).
      end if.
      compute dermat = {byzx2;bzx}.
      compute totse = sqrt(t(dermat)*varcov*dermat).
      compute specse = sqrt((byzx2&*byzx2)&*(avar)+(bzx&*bzx)&*(bvar)).
      compute specse = {totse; specse}.
      compute specz = {csum(indeff2);indeff2}&/specse.
      compute ind22 = {csum(indeff2);indeff2}.
      compute nms = {"TOTAL";nm(3:(nv-nc),1)}.
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute ind22 = {ind22;prws}.
        compute specse = {specse;prwse}.
        compute specz = {specz;(prws&/prwse)}.
        compute nms = {nms;cnam2}.
      end if.
      compute pspec= 2*(1-cdfnorm(abs(specz))).
      compute spec = {ind22, specse, specz, pspec}.
      print/title = "******************************************************************".
      print/title = "           NORMAL THEORY TESTS FOR INDIRECT EFFECTS".
      print spec/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Effect" "se" "Z" "p"/format = f9.4.
    end if.
  end if.
end loop.
RELEASE dd, dat, dat2, x, y, m, imat, resid.
do if (btn > 1).
  compute nms = {"TOTAL"; nm(3:(nv-nc),1)}.
  do if ((nv-nc-2) > 1 and (!contrast = 1)).
    compute crst = make((n+1+btn),((nv-nc-2)*(nv-nc-3)/2),0).
    compute kk=1.
    loop ic = 2 to (nv-nc-2).
      loop ic2 = (ic+1) to (nv-nc-1).
        compute crst(:,kk)=indeff(:,ic)-indeff(:,ic2).
        compute kk=kk+1.
      end loop.
    end loop.
    compute indeff = {indeff,crst}.
    compute cnam2 = cname(1:(kk-1),1).
    compute nms = {nms;cnam2}.
  end if.
compute lvout = indeff(2:(n+1),:).
compute tdotm = csum(lvout)/n.
compute tm = (make(n,ncol(lvout),1))*mdiag(tdotm).
compute topa = csum((((n-1)/n)*(tm-lvout))&**3).
compute bota = 6*sqrt((csum((((n-1)/n)*(tm-lvout))&**2)&**3)).
compute ahat = topa&/bota.
compute indsam = t(indeff(1,:)).
compute boot = indeff((n+2):nrow(indeff),:).
compute mnboot = t(csum(boot)/btn).
compute se = (sqrt(((btn*cssq(boot))-(csum(boot)&**2))/((btn-1)*btn))).
loop #e = 1 to ncol(indeff).
  compute boottmp = boot(:,#e).
  compute boottmp(GRADE(boot(:,#e))) = boot(:,#e).
  compute boot(:,#e) = boottmp.
end loop.
compute xp = make((nrow(mnboot)+2),1,0).
loop i = 1 to (nrow(mnboot)+2).
  do if (i <= nrow(mnboot)).
    compute pv = (boot(:,i) < indsam(i,1)).
    compute pv = csum(pv)/btn.
  else.
    compute pv = zbca((i-nrow(mnboot)),1).
  end if.
  compute p = pv.
  do if (pv > .5).
    compute p = 1-pv.
  end if.
  compute y5=sqrt(-2*ln(p)).
  compute xp(i,1)=y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0).
  do if (pv <= .5).
    compute xp(i,1) = -xp(i,1).
  end if.
end loop.
compute bbb = nrow(mnboot).
compute zz = xp(1:bbb,1).
compute zlo = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zup = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute ahat = 0.
compute zlobc = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zupbc = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute zlo = cdfnorm(zlo).
compute zup = cdfnorm(zup).
compute zlobc = cdfnorm(zlobc).
compute zupbc = cdfnorm(zupbc).
compute blow = trunc(zlo*(btn+1)).
compute bhigh = trunc(zup*(btn+1))+1.
compute blowbc = trunc(zlobc*(btn+1)).
compute bhighbc = trunc(zupbc*(btn+1))+1.
compute lowbca = make(nrow(blow),1,0).
compute upbca = lowbca.
loop i = 1 to nrow(blow).
  do if (blow(i,1) < 1).
    compute blow(i,1) = 1.
  end if.
  compute lowbca(i,1)=boot(blow(i,1),i).
  do if (bhigh(i,1) > btn).
    compute bhigh(i,1) = btn.
  end if.
  compute upbca(i,1)=boot(bhigh(i,1),i).
end loop.
compute lowbc = make(nrow(blow),1,0).
compute upbc = lowbca.
loop i = 1 to nrow(blowbc).
  do if (blowbc(i,1) < 1).
    compute blowbc(i,1) = 1.
  end if.
  compute lowbc(i,1)=boot(blowbc(i,1),i).
  do if (bhighbc(i,1) > btn).
    compute bhighbc(i,1) = btn.
  end if.
  compute upbc(i,1)=boot(bhighbc(i,1),i).
end loop.
print/title = "*****************************************************************".
print/title = "           BOOTSTRAP RESULTS FOR INDIRECT EFFECTS".
compute res = {indsam, mnboot,(mnboot-indsam), t(se)}.
print res/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Data" "Boot" "Bias" "SE"/format f9.4.
compute lowperc = boot(blowp,:).
compute upperc = boot(bhighp,:).
compute ci = {lowbca, upbca}.
do if (!bca <> 0).
  print ci/title = "Bias Corrected and Accelerated Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!bc <> 0).
  compute ci = {lowbc, upbc}.
  print ci/title = "Bias Corrected Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!percent <> 0).
  compute ci = {t(lowperc), t(upperc)}.
  print ci/title = "Percentile Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
print/title = "*****************************************************************".
print conf/title = "Level of Confidence for Confidence Intervals:".
print btn/title = "Number of Bootstrap Resamples:".
end if.
do if ((nv-nc-2) > 1 and (!contrast = 1) and ((!normal = 1 and nc = 0) OR btn > 999))).
print/title = "*****************************************************************".
print/title = "  INDIRECT EFFECT CONTRAST DEFINITIONS: Ind_Eff1 MINUS Ind_Eff2".
compute kk=1.
compute prwsv=make(((nv-nc-2)*(nv-nc-3)/2),2,0).
 loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
          compute prwsv(kk,1)=nm(ic+2,1).
          compute prwsv(kk,2)=nm(ic2+2,1).
          compute kk=kk+1.
       end loop.
end loop.
compute prwsv = {cnam2, prwsv}.
print prwsv/title = " "/clabels = "Contrast" "IndEff_1" "IndEff_2"/format A9.
end if.
Print/title = "********************************* NOTES **********************************".
do if (btn = 1 or !normal=1).
Print/title = "Bootstrap confidence intervals are preferred to normal theory tests for".
print/title = "inference about indirect effects.  See Hayes, A. F. (2009). Beyond Baron"/space=0.
print/title =  "and Kenny: Statistical mediation analysis in the new millennium."/space=0.
Print/title = "Communication Monographs, 76, 408-420, or Hayes, A. F. (2013). Introduction to"/space=0.
print/title = "mediation, moderation, and conditional process analysis: A regression-based"/space=0.
print/title = "approach. New York: The Guilford Press"/space=0.
end if.
do if (bdbp > 0).
print/title = "*****************************************************************".
print/title = "WARNING: SOME BOOTSTRAP MATRICES WERE SINGULAR".
print/title = "SINGULAR MATRICES WERE REPLACED DURING RESAMPLING".
print bdbp/title = "Number of singular bootstrap samples replaced:".
end if.
   do if (ovals = 2).
   print/title = "*****************************************************************".
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE FOR MODELS WITH DICHOTOMOUS OUTCOMES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
   do if (nc > 0 and !normal = 1).
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE IN MODELS WITH COVARIATES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
END MATRIX.
RESTORE.
!ENDDEFINE.
INDIRECT y = AngerIngroupFRDiv100/x = PartyInd/m = PersBenefitsDiv100 ValuesImportantDiv100 PastContributionsDiv100 NationBenefitsDiv100 AngerOutgroupFRDiv100 
partSex raceBlack raceOther raceHispanic raceTwoPlus AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded/boot = 10000/conf = 95/normal = 1/contrast = 0/percent = 1/bc = 1/bca = 1.

/* Written by Andrew F. Hayes */.
/* http://www.afhayes.com */.
/* Version 4.2 */.
DEFINE INDIRECT (y = !charend('/')/x = !charend('/')/m = !charend('/')/c=!charend('/') !default(xxxxx)/
  boot =!charend('/') !default(1000)/conf = !charend('/') !default(95)/percent = !charend('/') !default(0)/bc = !charend('/')
  !default(1)/bca = !charend('/') !default(0)/normal = !charend ('/') !default(0)/contrast = !charend ('/') !default(0)/iterate = !charend('/') !default(10000)/converge =
  !charend('/') !default(.0000001)).
PRESERVE.
SET LENGTH = NONE.
SET MXLOOPS = 10000001.
SET SEED = RANDOM.
SET PRINTBACK = OFF.
MATRIX.
get dd/variables = !y !x !m/names = nm/MISSING = OMIT.
compute temp = ncol(dd).
get dd2/variables = !y !x PersBenefitsDiv100/MISSING = OMIT.
compute nc = ncol(dd)-ncol(dd2).
compute ovals = ncol(design(dd(:,1))).
do if (ovals = 2).
   compute omx = cmax(dd(:,1)).
   compute omn = cmin(dd(:,1)).
   compute dd(:,1) = (dd(:,1) = omx).
   compute rcd = {omn, 0; omx, 1}.
end if.
compute nm = t(nm).
compute outv = t(nm(1,1)).
compute n = nrow(dd).
compute nv = ncol(dd).
compute con = make(n,1,1).
compute dat2 = dd.
compute dat = dd.
compute bzx = make(nv-2-nc,1,0).
compute bzxse = make(nv-2-nc,1,0).
compute b=make((nv-1-nc),(nv-1-nc),0).
compute resid = make(n,(nv-nc),0).
compute info = make((2*(nv-nc-2)+1),(2*(nv-nc-2)+1),0).
compute imat = make(ncol(info),4,1).
compute imat(1:(nv-nc-2),1)=t({2:(nv-nc-1):1}).
compute imat(1:(nv-nc-2),3)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),2)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),4)=t({2:(nv-nc-1):1}).
compute imat((nv-nc-1):(ncol(info)-1),1)=make((nv-nc-2),1,(nv-nc)).
compute imat((nv-nc-1):(ncol(info)-1),3)=make((nv-nc-2),1,(nv-nc)).
compute imat(ncol(info),:)={(nv-nc),1,(nv-nc),1}.
compute cname={"C1";"C2";"C3";"C4";"C5";"C6";"C7";"C8";"C9";"C10";"C11";"C12";"C13";"C14";"C15";"C16";"C17"}.
compute cname={cname;"C18";"C19";"C20";"C21";"C22";"C23";"C24";"C25";"C26";"C27";"C28";"C29";"C30";"C31"}.
compute cname={cname;"C32";"C33";"C34";"C35";"C36";"C37";"C38";"C39";"C40";"C41";"C42";"C43";"C44";"C45"}.
compute p0=-.322232431088.
compute p1 = -1.
compute p2 = -.342242088547.
compute p3 = -.0204231210245.
compute p4 = -.0000453642210148.
compute q0 = .0993484626060.
compute q1 = .588581570495.
compute q2 = .531103462366.
compute q3 = .103537752850.
compute q4 = .0038560700634.
compute conf = rnd(!conf).
compute lowalp = 0.5*(1-(conf/100)).
compute upalp = 0.5*(1+(conf/100)).
compute zbca = {lowalp; upalp}.
do if (!boot > 999).
   compute btn = trunc(!boot/1000)*1000.
   compute lpmax = n+1+btn.
   else.
   compute btn = 1.
   compute lpmax = 1.
end if.
compute blowp = trunc(lowalp*btn).
do if (blowp < 1).
  compute blowp = 1.
end if.
compute bhighp = trunc((upalp*btn)+1).
do if (bhighp > btn).
  compute bhighp = btn.
end if.
compute indeff = make(n+1+btn,nv-1-nc,-9999).
compute bdbp = 0.
loop #d = 1 to lpmax.
   do if (#d = (n+2)).
    compute dat = dat2.
    compute con = make(n,1,1).
  end if.
  do if (#d > 1 and #d < (n+2)).
    do if (#d = 2).
      compute con = make((n-1),1,1).
      compute dat = dat2(2:n,:).
    else if (#d = (n+1)).
      compute dat = dat2(1:(n-1),:).
    else.
      compute dat = {dat2(1:(#d-2),:);dat2((#d:n),:)}.
    end if.
  end if.
  do if (#d > (n+1)).
    loop.
    compute v=trunc(uniform(n,1)*n)+1.
    compute dat(:,1:nv) = dat2(v,1:nv).
    compute dat3 = {con,dat(:,2:ncol(dat))}.
    compute rk = (rank(dat3)=ncol(dat3)).
    compute bdbp = bdbp+(1-rk).
    end loop if (rk = 1).
  end if.
  compute x = dat(:,2).
  compute m = dat(:,3:(nv-nc)).
  compute y = dat(:,1).
  compute xz = dat(:,2:nv).
  compute xo = {con,x}.
  do if (nc > 0).
    compute c = dat(:,(nv-nc+1):nv).
    compute xo = {xo, c}.
  end if.
  loop #k = 3 to (nv-nc).
     compute ytmp = dat(:,#k).
     compute bzxt = inv(t(xo)*xo)*t(xo)*ytmp.
     compute bzx((#k-2),1)=bzxt(2,1).
     do if (#d = 1).
       compute resid(:,#k-1) = ytmp-(xo*bzxt).
       compute mse=csum((ytmp-(xo*bzxt))&**2)/(n-2-nc).
       compute olscm=(mse*inv((t(xo)*xo))).
       compute bzxse((#k-2),1)=sqrt(olscm(2,2)).
     end if.
  end loop.
  do if (#d = 1).
    do if (nc > 0).
      compute cnt = dd(:,(nv-(nc-1)):nv)).
      compute xo = {con,x,cnt}.
    else.
      compute xo = {con,x}.
    end if.
   do if (ovals = 2).
   compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
   compute pt1 = make(nrow(y),1,0.5).
   compute bt1 = make(ncol(xo),1,0).
   compute LL1 = 0.
   loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byx = bt1+inv(t(xo)*vt1*xo)*t(xo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xo*byx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xo)*vt1*xo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byx.
    compute LL1 = LL2.
    end loop.
    compute byx = byx(2,1).
    compute byxse = sqrt(olscm(2,1)).
    do if (jjj > !iterate).
     compute itprob = 2.
    end if.
  end if.
    do if (ovals <> 2).
    compute byx = inv(t(xo)*xo)*t(xo)*y.
    compute mse=csum((y-(xo*byx))&**2)/(n-2-nc).
    compute olscm=(mse*inv((t(xo)*xo))).
    compute byxse = sqrt(olscm(2,2)).
    compute byx = byx(2,1).
    end if.
  end if.
  compute xzo = {con,xz}.
do if (ovals = 2).
compute pt2 = make(nrow(y),1,(csum(y)/nrow(y))).
compute LL3 = y&*ln(pt2)+(1-y)&*ln(1-pt2).
compute LL3 = -2*csum(LL3).
compute pt1 = make(nrow(y),1,0.5).
  compute bt1 = make(ncol(xzo),1,0).
  compute LL1 = 0.
  loop jjj = 1 to !iterate.
    compute vt1 = mdiag(pt1&*(1-pt1)).
    compute byzx = bt1+inv(t(xzo)*vt1*xzo)*t(xzo)*(y-pt1).
    compute pt1 = 1/(1+exp(-(xzo*byzx))).
    compute itprob = csum((pt1 < .00000000000001) or (pt1 > .99999999999999)).
    do if (itprob = 0).
    compute LL = y&*ln(pt1)+(1-y)&*ln(1-pt1).
    compute LL2 = -2*csum(ll).
    end if.
    do if (abs(LL1-LL2) < !converge).
      compute vt1 = mdiag(pt1&*(1-pt1)).
      compute varb = inv(t(xzo)*vt1*xzo).
      compute olscm = diag(varb).
      break.
    end if.
    compute bt1 = byzx.
    compute LL1 = LL2.
  end loop.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    do if (#d = 1).
    compute pi = (exp(xzo*byzx)/(1+exp(xzo*byzx))).
    compute resid(:,ncol(resid))=((y-pt1)/abs(y-pt1))&*sqrt(-2*(LL)).
    end if.
do if (jjj > !iterate).
   compute itprob = 2.
end if.
end if.
  do if (ovals <> 2).
  compute byzx = inv(t(xzo)*xzo)*t(xzo)*y.
  compute byzx2 = byzx(3:(nv-nc),1).
  do if (#d = 1).
    compute mse=csum((y-(xzo*byzx))&**2)/(n-nv).
    compute resid(:,ncol(resid))=y-(xzo*byzx).
    compute covmat=mse*inv(t(xzo)*xzo).
    compute olscm=diag(covmat).
    compute sse = mse*(n-nv).
    compute sst = csum((y-(csum(y)/n))&**2).
    compute r2 = 1-(sse/sst).
    compute ar2 = 1-(mse/(sst/(n-1))).
    compute fr = ((n-nv)*r2)/((1-r2)*ncol(xz)).
    compute pfr = 1-fcdf(fr,ncol(xz),(n-nv)).
    do if (nc > 0).
      compute bcon = byzx((nv-nc+1):nv,1).
      compute bconse = sqrt(olscm((nv-nc+1):nv,1)).
    end if.
    compute byzx2se = sqrt(olscm(3:(nv-nc),1)).
    compute cprime = byzx(2,1).
    compute cprimese = sqrt(olscm(2,1)).
  end if.
  end if.
  compute indeff2 = (bzx&*byzx2).
  compute zs = (bzx&/bzxse)&*(byzx2&/byzx2se).
  compute temp = t({csum(indeff2); indeff2}).
  compute indeff(#d,:) = temp.
  do if (#d = 1).
    compute vs = nm(1:(nv-nc),1).
    print/title = "*****************************************************************".
    print/title = "Preacher and Hayes (2008) SPSS Macro for Multiple Mediation"/space=0.
    print/title = "Written by Andrew F. Hayes, The Ohio State University"/space=0.
    print/title = "www.afhayes.com"/space=0.
    print/title = "For details, see Preacher, K. J., & Hayes, A. F. (2008). Asymptotic"/space=0.
    print/title = "and resampling strategies for assessing and comparing indirect effects"/space=0.
    print/title = "in multiple mediator models. Behavior Research Methods, 40, 879-891."/space=0.
    print/title = "Also see Chapter 5 of Introduction to Mediation, Moderation, and Conditional"/space=0.
    print/title = "Analysis.  New York: The Guilford Press.  http://www.guilford.com/p/hayes3"/space=0.
    print/title = "*****************************************************************"/space=0.
    print vs/title = "Dependent, Independent, and Proposed Mediator Variables:"/rlabels = "DV =" "IV = " "MEDS = "/format a8.
    do if (nc > 0).
      compute vs = nm((nv-nc+1):nv,1).
      print vs/title = "Statistical Controls:"/rlabels = "CONTROL="/format a8.
    end if.
    print n/title = "Sample size"/format F10.0.
    do if (ovals = 2).
    compute nmsd = {outv, "Analysis"}.
    print rcd/title = "Coding of binary DV for analysis:"/cnames = nmsd/format = F9.2.
    end if.
    compute nms = nm(3:(nv-nc),1).
    compute te = bzx&/bzxse.
    compute df = n-2-nc.
    compute p = 2*(1-tcdf(abs(te), df)).
    compute bzxmat = {bzx, bzxse,te,p}.
    compute b(2:(nv-1-nc),1)=bzx.
    compute se2 = bzxse&*bzxse.
    print bzxmat/title = "IV to Mediators (a paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    compute te = byzx2&/byzx2se.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byzx2mat={byzx2, byzx2se, te, p}.
    print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute byzx2mat={byzx2, byzx2se, te, p, Wald}.
      print byzx2mat/title = "Direct Effects of Mediators on DV (b paths)"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = byx&/byxse.
    compute df = n-2-nc.
    compute xnm = nm(2,1).
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute byxmat = {byx, byxse, te, p}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute byxmat = {byx, byxse, te, p, Wald}.
    print byxmat/title = "Total Effect of IV on DV (c path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    compute te = cprime&/cprimese.
    compute df = n-nv.
    do if (ovals <> 2).
    compute p = 2*(1-tcdf(abs(te), df)).
    compute cprimmat = {cprime, cprimese, te, p}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "t" "p"/format f9.4.
    end if.
    do if (ovals = 2).
    compute wald = te&*te.
    compute p = 2*(1-cdfnorm(abs(te))).
    compute cprimmat = {cprime, cprimese, te, p, Wald}.
    print cprimmat/title = "Direct Effect of IV on DV (c' path)"/rnames = xnm/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
    end if.
    do if (nc > 0).
      compute df = n-nv.
      compute nms = nm((nv-nc+1):nv,1).
      compute te = bcon&/bconse.
      do if (ovals <> 2).
      compute p = 2*(1-tcdf(abs(te), df)).
      compute bconmat = {bcon, bconse,te,p}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "t" "p"/format f9.4.
      end if.
      do if (ovals = 2).
      compute wald = te&*te.
      compute p = 2*(1-cdfnorm(abs(te))).
      compute bconmat = {bcon, bconse,te,p, Wald}.
      print bconmat/title = "Partial Effect of Control Variables on DV"/rnames = nms/clabels "Coeff" "se" "Z" "p" "Wald"/format f9.4.
      end if.
    end if.
    do if (ovals <> 2).
    compute dvms = {r2, ar2, fr, ncol(xz), (n-nv), pfr}.
    print dvms/title = "Model Summary for DV Model"/clabels "R-sq" "Adj R-sq" "F" "df1" "df2" "p"/format F9.4.
    end if.
   do if (ovals = 2).
   compute LLdiff = LL3-LL2.
   compute mcF = LLdiff/LL3.
   compute cox = 1-exp(-LLdiff/n).
   compute nagel = cox/(1-exp(-(LL3)/n)).
   compute pf = {LL2, LLdiff, mcF, cox, nagel, n}.
   print pf/title = "Logistic Regression Summary for DV Model"/clabels = "-2LL" "Model LL" "McFadden" "CoxSnell" "Nagelkrk" "n"/format F10.4.
   end if.
    do if (!normal <> 0 and nc = 0 and ovals <> 2).
      compute bmat = make((nv-nc),(nv-nc),0).
      compute bmat(2:(nv-nc-1),1) = bzx.
      compute bmat((nv-nc),2:(nv-nc-1))=t(byzx2).
      compute bmat((nv-nc),1) = cprime.
      compute imbinv = inv(ident(ncol(bmat))-bmat).
      compute imbtinv=inv(ident(ncol(bmat))-t(bmat)).
      compute resid(:,1)=x-(csum(x)/(n)).
      compute psi = sscp(resid)/(n).
      compute invpsi = inv(psi).
      compute ibpsiib = imbinv*psi*imbtinv.
      loop ic = 1 to ncol(info).
      loop ic2 = 1 to ncol(info).
      compute info(ic,ic2)=(n-1)*((imbinv(imat(ic2,4),imat(ic,1))*imbinv(imat(ic,2),imat(ic2,3)))+(ibpsiib(imat(ic2,4),imat(ic,2))*invpsi(imat(ic,1),imat(ic2,3)))).
      end loop.
      end loop.
      compute varcov = inv(info).
      compute varcov = varcov(1:(2*(nv-nc-2)),1:(2*(nv-nc-2))).
      compute ses = diag(varcov).
      compute avar = ses(1:nrow(bzxse),1).
      compute bvar = ses((nrow(bzxse)+1):nrow(ses),1).
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute prws=make(((nv-nc-2)*(nv-nc-3)/2),1,0).
        compute prwse=prws.
        compute kk=1.
        loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
        compute vf2 = ((byzx2(ic,1)**2)*varcov(ic,ic))-(2*byzx2(ic,1)*byzx2(ic2,1)*(varcov(ic,ic2))).
        compute vf2=vf2+((byzx2(ic2,1)**2)*varcov(ic2,ic2))+((bzx(ic,1)**2)*(bvar(ic,1))).
        compute vf2=vf2-(2*bzx(ic,1)*bzx(ic2,1)*covmat((2+ic),(2+ic2)))+((bzx(ic2,1)**2)*(bvar(ic2,1))).
        compute cnt = indeff2(ic,1)-indeff2(ic2,1).
        compute prws(kk,1)=cnt.
        compute prwse(kk,1)=sqrt(vf2).
        compute kk=kk+1.
        end loop.
        end loop.
        compute cnam2 = cname(1:(kk-1),1).
      end if.
      compute dermat = {byzx2;bzx}.
      compute totse = sqrt(t(dermat)*varcov*dermat).
      compute specse = sqrt((byzx2&*byzx2)&*(avar)+(bzx&*bzx)&*(bvar)).
      compute specse = {totse; specse}.
      compute specz = {csum(indeff2);indeff2}&/specse.
      compute ind22 = {csum(indeff2);indeff2}.
      compute nms = {"TOTAL";nm(3:(nv-nc),1)}.
      do if ((nv-nc-2) > 1 and (!contrast = 1)).
        compute ind22 = {ind22;prws}.
        compute specse = {specse;prwse}.
        compute specz = {specz;(prws&/prwse)}.
        compute nms = {nms;cnam2}.
      end if.
      compute pspec= 2*(1-cdfnorm(abs(specz))).
      compute spec = {ind22, specse, specz, pspec}.
      print/title = "******************************************************************".
      print/title = "           NORMAL THEORY TESTS FOR INDIRECT EFFECTS".
      print spec/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Effect" "se" "Z" "p"/format = f9.4.
    end if.
  end if.
end loop.
RELEASE dd, dat, dat2, x, y, m, imat, resid.
do if (btn > 1).
  compute nms = {"TOTAL"; nm(3:(nv-nc),1)}.
  do if ((nv-nc-2) > 1 and (!contrast = 1)).
    compute crst = make((n+1+btn),((nv-nc-2)*(nv-nc-3)/2),0).
    compute kk=1.
    loop ic = 2 to (nv-nc-2).
      loop ic2 = (ic+1) to (nv-nc-1).
        compute crst(:,kk)=indeff(:,ic)-indeff(:,ic2).
        compute kk=kk+1.
      end loop.
    end loop.
    compute indeff = {indeff,crst}.
    compute cnam2 = cname(1:(kk-1),1).
    compute nms = {nms;cnam2}.
  end if.
compute lvout = indeff(2:(n+1),:).
compute tdotm = csum(lvout)/n.
compute tm = (make(n,ncol(lvout),1))*mdiag(tdotm).
compute topa = csum((((n-1)/n)*(tm-lvout))&**3).
compute bota = 6*sqrt((csum((((n-1)/n)*(tm-lvout))&**2)&**3)).
compute ahat = topa&/bota.
compute indsam = t(indeff(1,:)).
compute boot = indeff((n+2):nrow(indeff),:).
compute mnboot = t(csum(boot)/btn).
compute se = (sqrt(((btn*cssq(boot))-(csum(boot)&**2))/((btn-1)*btn))).
loop #e = 1 to ncol(indeff).
  compute boottmp = boot(:,#e).
  compute boottmp(GRADE(boot(:,#e))) = boot(:,#e).
  compute boot(:,#e) = boottmp.
end loop.
compute xp = make((nrow(mnboot)+2),1,0).
loop i = 1 to (nrow(mnboot)+2).
  do if (i <= nrow(mnboot)).
    compute pv = (boot(:,i) < indsam(i,1)).
    compute pv = csum(pv)/btn.
  else.
    compute pv = zbca((i-nrow(mnboot)),1).
  end if.
  compute p = pv.
  do if (pv > .5).
    compute p = 1-pv.
  end if.
  compute y5=sqrt(-2*ln(p)).
  compute xp(i,1)=y5+((((y5*p4+p3)*y5+p2)*y5+p1)*y5+p0)/((((y5*q4+q3)*y5+q2)*y5+q1)*y5+q0).
  do if (pv <= .5).
    compute xp(i,1) = -xp(i,1).
  end if.
end loop.
compute bbb = nrow(mnboot).
compute zz = xp(1:bbb,1).
compute zlo = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zup = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute ahat = 0.
compute zlobc = zz + ((zz+xp((bbb+1),1))&/(1-t(ahat)&*(zz+xp((bbb+1),1)))).
compute zupbc = zz + ((zz+xp((bbb+2),1))&/(1-t(ahat)&*(zz+xp((bbb+2),1)))).
compute zlo = cdfnorm(zlo).
compute zup = cdfnorm(zup).
compute zlobc = cdfnorm(zlobc).
compute zupbc = cdfnorm(zupbc).
compute blow = trunc(zlo*(btn+1)).
compute bhigh = trunc(zup*(btn+1))+1.
compute blowbc = trunc(zlobc*(btn+1)).
compute bhighbc = trunc(zupbc*(btn+1))+1.
compute lowbca = make(nrow(blow),1,0).
compute upbca = lowbca.
loop i = 1 to nrow(blow).
  do if (blow(i,1) < 1).
    compute blow(i,1) = 1.
  end if.
  compute lowbca(i,1)=boot(blow(i,1),i).
  do if (bhigh(i,1) > btn).
    compute bhigh(i,1) = btn.
  end if.
  compute upbca(i,1)=boot(bhigh(i,1),i).
end loop.
compute lowbc = make(nrow(blow),1,0).
compute upbc = lowbca.
loop i = 1 to nrow(blowbc).
  do if (blowbc(i,1) < 1).
    compute blowbc(i,1) = 1.
  end if.
  compute lowbc(i,1)=boot(blowbc(i,1),i).
  do if (bhighbc(i,1) > btn).
    compute bhighbc(i,1) = btn.
  end if.
  compute upbc(i,1)=boot(bhighbc(i,1),i).
end loop.
print/title = "*****************************************************************".
print/title = "           BOOTSTRAP RESULTS FOR INDIRECT EFFECTS".
compute res = {indsam, mnboot,(mnboot-indsam), t(se)}.
print res/title = "Indirect Effects of IV on DV through Proposed Mediators (ab paths)"/rnames = nms/clabels "Data" "Boot" "Bias" "SE"/format f9.4.
compute lowperc = boot(blowp,:).
compute upperc = boot(bhighp,:).
compute ci = {lowbca, upbca}.
do if (!bca <> 0).
  print ci/title = "Bias Corrected and Accelerated Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!bc <> 0).
  compute ci = {lowbc, upbc}.
  print ci/title = "Bias Corrected Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
do if (!percent <> 0).
  compute ci = {t(lowperc), t(upperc)}.
  print ci/title = "Percentile Confidence Intervals"/rnames = nms/clabels "Lower" "Upper"/format F9.4.
end if.
print/title = "*****************************************************************".
print conf/title = "Level of Confidence for Confidence Intervals:".
print btn/title = "Number of Bootstrap Resamples:".
end if.
do if ((nv-nc-2) > 1 and (!contrast = 1) and ((!normal = 1 and nc = 0) OR btn > 999))).
print/title = "*****************************************************************".
print/title = "  INDIRECT EFFECT CONTRAST DEFINITIONS: Ind_Eff1 MINUS Ind_Eff2".
compute kk=1.
compute prwsv=make(((nv-nc-2)*(nv-nc-3)/2),2,0).
 loop ic = 1 to (nv-nc-3).
        loop ic2 = (ic+1) to (nv-nc-2).
          compute prwsv(kk,1)=nm(ic+2,1).
          compute prwsv(kk,2)=nm(ic2+2,1).
          compute kk=kk+1.
       end loop.
end loop.
compute prwsv = {cnam2, prwsv}.
print prwsv/title = " "/clabels = "Contrast" "IndEff_1" "IndEff_2"/format A9.
end if.
Print/title = "********************************* NOTES **********************************".
do if (btn = 1 or !normal=1).
Print/title = "Bootstrap confidence intervals are preferred to normal theory tests for".
print/title = "inference about indirect effects.  See Hayes, A. F. (2009). Beyond Baron"/space=0.
print/title =  "and Kenny: Statistical mediation analysis in the new millennium."/space=0.
Print/title = "Communication Monographs, 76, 408-420, or Hayes, A. F. (2013). Introduction to"/space=0.
print/title = "mediation, moderation, and conditional process analysis: A regression-based"/space=0.
print/title = "approach. New York: The Guilford Press"/space=0.
end if.
do if (bdbp > 0).
print/title = "*****************************************************************".
print/title = "WARNING: SOME BOOTSTRAP MATRICES WERE SINGULAR".
print/title = "SINGULAR MATRICES WERE REPLACED DURING RESAMPLING".
print bdbp/title = "Number of singular bootstrap samples replaced:".
end if.
   do if (ovals = 2).
   print/title = "*****************************************************************".
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE FOR MODELS WITH DICHOTOMOUS OUTCOMES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
   do if (nc > 0 and !normal = 1).
   print/title = "NORMAL THEORY TESTS NOT AVAILABLE IN MODELS WITH COVARIATES".
   do if (!boot = 0).
   print/title = "To obtain indirect effects, request bootstrapping".
   end if.
   end if.
END MATRIX.
RESTORE.
!ENDDEFINE.
INDIRECT y = GratIngroupConDiv100/x = PartyInd/m = PersBenefitsDiv100 ValuesImportantDiv100 partSex raceBlack raceOther raceHispanic raceTwoPlus 
AgeDiv100 Education0To1 IncomeRecoded RightToLeftPoliticsRecoded PastContributionsDiv100 GratOutgroupConDiv100 NationBenefitsDiv100/boot = 10000/conf = 95/normal = 1/contrast = 0/percent = 1/bc = 1/bca = 1.
